Fair Classification
Fair Classification is a methodological framework in machine learning that integrates fairness constraints or criteria into the classification process to mitigate discriminatory outcomes against sensitive attributes while maintaining predictive utility.
229
Publications
20.2K
Citations
667
Authors
238
Institutions
Publications per year
2017–2026
206
Parents
229
Cynthia Dwork, Moritz Hardt, Toniann Pitassi et al. · 2012 · 3.4K citations
Fairness definitions explained
Sahil Verma, Julia Rubin · 2018 · 1.1K citations
Rich Zemel, Yu Wu, Kevin Swersky et al. · 2013 · 1K citations
Fairness Beyond Disparate Treatment & Disparate Impact
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez-Rodriguez et al. · 2017 · 616 citations · Full text
1–5 of 229
667
Max Planck Institute for Software Systems, Germany
10 publications · 2.1K citations
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8
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7
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7
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1–5 of 667
238

Cornell University
Ithaca, United States
12 h-index
34 publications
2.8K citations
Max Planck Institute for Software Systems
Saarbrücken, Germany
10 h-index
35 publications
8K citations
Google (United States)
Mountain View, United States
10 h-index
37 publications
3.5K citations

University of Toronto
Toronto, Canada
9 h-index
28 publications
12.4K citations
University of Pennsylvania
Philadelphia, United States
8 h-index
17 publications
2K citations
Max Planck Society
Munich, Germany
7 h-index
27 publications
3.4K citations

Harvard University Press
Cambridge, United States
6 h-index
8 publications
882 citations
Microsoft (United States)
Redmond, United States
6 h-index
10 publications
8.2K citations
1–8 of 238
Repository · 68 publications · 4.6K citations
27
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Conference · 14 publications · 517 citations
13
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Repository · 5 publications · 781 citations
5
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Repository · 4 publications · 427 citations
4
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Conference · 3 publications · 94 citations
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